Conference Session

Student Attitudes and Perceptions

Collection

2010 Annual Conference & Exposition

Authors

Tuba Yildirim, University of Pittsburgh; Mary Besterfield-Sacre, University of Pittsburgh; Larry Shuman, University of Pittsburgh

Tagged Divisions

Educational Research and Methods

iterations and updates to their solution methodology (process). A student with highlevels of self-efficacy should, in theory, persist longer in modeling iterations and perform betterin creation of conceptual and calculational models. In contrast, low self-efficacy may inhibit thestudent’s effort even when the skill is present leading to discouragement.A common approach to measure self-efficacy, particularly in the context of student work, hasbeen to ask students to what extent they believe they can perform a certain task. However, asself-efficacy is task dependent and there is no common single method to measure it, we proposethat a separate scale needs to be developed for modeling. This is particularly true forengineering students; as how self

Collection

2010 ASEE Zone 4 Conference

Authors

A.M. Vollstedt; E. L. Wang

scales, oneshould make sure they are measuring self efficacy, or belief in one‟s capability, not self esteem,which is belief in one‟s self. The standard method for constructing a self efficacy survey is toask individuals to rate their belief in their ability to perform a specific task. Subjects rate theirefficacy on a likert scale that ranges from zero or no confidence to 100 or high confidence.Cognition is the process of knowing, applying knowledge, and changing preferences. There aretwo popular methods for measuring cognitive levels including Perry‟s Model and King andKitchener‟s Reflective Judgment (RJ) model. Both models are similar in classification althoughPerry‟s model contains two extra positions at the higher end of the scale 6, 7

Conference Session

New Learning Paradigms II

Collection

2010 Annual Conference & Exposition

Authors

Chandra Austin, Utah State University

Tagged Divisions

Educational Research and Methods

has confidence in his orher ability to engage in occupational and educational decision making 17. Career decision self-efficacy, which was originally defined by Taylor and Betz 18, is measured in terms of self-appraisal, occupational information, goal selection, planning, and problem-solving 19. Qualityexploration of career development is the basis for career decision self-efficacy 16. Research hasused the Social Cognitive Career Theory (SCCT)20 and outcome expectations to predictbehavioral influences in careers. Ojeda et al. 21 reported that high levels of confidence are relatedto positive career behaviors and outcomes. Thus, there is no debate that behavior stronglyinfluences career decision self-efficacy. The interest comes when one

Conference Session

Retaining Women Engineering Students

Collection

2010 Annual Conference & Exposition

Authors

Rachelle Reisberg, Northeastern University; Margaret Bailey, Rochester Institute of Technology; Carol Burger, Virginia Tech; Jerry Hamann, University of Wyoming; Joe Raelin, Northeastern University; David Whitman, University of Wyoming

Tagged Divisions

Women in Engineering

-efficacy through the impact of contextual support.Self-efficacy was assessed through three measures – work, career, and academic – signifying the Page 15.1223.3confidence that students have in succeeding within the workplace, within their chosenengineering career, or in the classroom, respectively. Contextual support was measured as thesupport provided to students through a number of mechanisms, in particular, financial aid,mentors, advisors, family, friends, teachers, profession, campus life, and living/learningcommunities.This paper will present the survey methodology, the results to date regarding the effect of genderon self-efficacy through

Collection

2010 ASEE Zone 4 Conference

Authors

Oenardi Lawanto

, particularly at the Proceedings of the 2010 American Society for Engineering Education Zone IV Conference Copyright © 2010, American Society for Engineering Education 356precollege level.The focus of this study is to answer one broad question: Is there a significant correlation betweenstudents’ goal orientation (GO) and their self-efficacy for learning and performance (SELP)? Inthis study, students’ goal orientation was measured through constructs such as intrinsic andextrinsic goal orientations. Students’ self-efficacy for learning and performance was used toindicate students’ self-efficacy and expectancy for success

Conference Session

Measurement Tools

Collection

2010 Annual Conference & Exposition

Authors

Adam Carberry, Tufts University; Matthew Ohland, Purdue University; Chris Swan, Tufts University

Tagged Divisions

Educational Research and Methods

writing self-efficacy assessment: Greater discrimination increases prediction. Measurement and Evaluation in Counseling and Development, 2001. 33: p. 214-221.32. Comrey, A.L. and J.W. Osborne, Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, & Evaluation, 2005. 10(7).33. Gorsuch, R.L., Factor analysis. 2nd ed. 1983, Hillsdale, NJ: Earlbaum.34. MacCallum, R.C., et al., Sample size in factor analysis. Psychological Methods, 1999. 4: p. 84-99.35. Rummel, R.J., Applied factor analysis. 1970, Evanston, IL: Northwestern University Press.36. Stevens, R., K. O'Connor, and L. Garrison. Engineering student identities in the navigation of the

Conference Session

Post BS Entrepreneurship Education Needs

Collection

2010 Annual Conference & Exposition

Authors

Andrew Borchers, Kettering University; Sung Hee Park, Kettering University; Michael Harris, Kettering University; William Riffe, Kettering University; Massoud Tavakoli, Kettering University

Tagged Divisions

Entrepreneurship & Engineering Innovation

somewhat amorphous concept such as entrepreneurial thinking and mindset. In this paper, the authors describe Kettering University’s efforts to measure faculty and student attitudes as we seek to infuse entrepreneurship across the curriculum. The paper discusses three specific measurement efforts. Our early efforts were formative and focused on student entrepreneurial mindset among engineering students studying entrepreneurship in a single course. Here we used measures of self-efficacy and locus of control as predictors of intention to start a business 2 3 4. Our second (and current) efforts focus on a pilot project designed to motivate faculty to alter their courses to include one or more of eleven

Conference Session

Understanding and Measuring the Impact of Multidisciplinarity

Collection

2010 Annual Conference & Exposition

Authors

Scott Schaffer, Purdue University; Daniel Gandara, Illinois Institute of Technology; Xiaojun Chen, Purdue University; Margaret Huyck, Illinois Institute of Technology; Jill May, Illinois Institute of Technology

Tagged Divisions

Multidisciplinary Engineering

pilot study shows that students' self-efficacy for specific cross-disciplinary team learning objectives was influenced by participation on team projects withothers from different disciplines. Further data collection will help better understand how teamcomposition, stage of project design, and individual factors such as year in school and priorexperience with similar projects impacts confidence levels.II. Development of cross-disciplinary team functioning measuresThe team also attempts to develop and measure teamwork in cross-disciplinary projectteams. Such teams consist of members with different functional experiences and abilities, andwill likely come from different departments within the organization 13. Many believe that inorder for

Conference Session

Mentoring Graduate Students, Diversity, and Assessment

Collection

2010 Annual Conference & Exposition

Authors

Stephen Thompson, University of South Carolina; Joy Watson, University of South Carolina; Jed Lyons, University of South Carolina

Tagged Divisions

Graduate Studies

been widely used to measurethe Science teaching efficacy of various teacher groups. A modified version of the STEBI-B wasused in this study. STEBI-B pre and post-study results (25-item survey) were obtained for 23GK-12 Fellows (13 in 2007-8 and 10 in 2008-9). Pre and post focus group data were alsoanalyzed using qualitative data analysis techniques. The STEBI-B contains two subscales.Personal Science Teaching Efficacy (PSTE) which captures the construct of self-efficacy andScience Teaching Outcome Expectancy (STOE) which measures outcome expectancy regardingScience teaching and learning. A dependent t-test, using an alpha of .05, was computed for thetwo subscales to determine if there was a significant difference between the mean scores for

Conference Session

Engineering in the Middle Grades

Collection

2010 Annual Conference & Exposition

Authors

Morgan Hynes, Tufts University; David Crismond, The City College of New York; Ethan Danahy, Tufts University

Tagged Divisions

K-12 & Pre-College Engineering

can lead to less effectivecurriculum implementation, and, even worse, lower student efficacy in that content area 20.The project team did not have a validated tool to measure the teachers’ EDP content knowledge,but were able to use a newly validated tool to measure the teachers EDP. The EngineeringDesign Self-efficacy Survey developed by Carberryet al.21measures one’s self-efficay,motivation, expectancy, and anxiety towards carrying out the EDP. The tool was developed todiscern individuals self-efficacy towards the EDP and was applied to groups ranging from littleto no engineering background to experts in the field (professional engineers and engineeringprofessors).ResultsThe teachers who participated in the summer workshop each took the

Conference Session

Special Session: Impacts of Service in Engineering

Collection

2010 Annual Conference & Exposition

Authors

Trevor Harding, California Polytechnic State University; Lynne Slivovsky, California Polytechnic State University; Nina Truch, California Polytechnic State University

Tagged Divisions

Educational Research and Methods

the psychological constructs are shown in Table 2. Eachconstruct was measured with at least one instrument, but in some cases several such instrumentswere used. For example, we defined self-efficacy as the belief that one is capable of performinga certain task or tasks in order to achieve a desired goal. From this definition, it is apparent thatany measure of self-efficacy would be highly dependent on the tasks and goals in question. AsTable 1 indicates, we were interested in assessing students’ self-efficacy surrounding both designand life-long learning. A review of the literature failed to produce validated instruments foreither objective. Consequently, we developed our own instrument based on the work of AlbertBandura.9 As Table 2 shows

Collection

2010 ASEE Zone 1 Conference

Authors

Jeanine Lee Skorinko; Jennifer Lay; Grant McDonald; Brad Miller; Colleen Shaver; Cindy Randall; James Kevin Doyle; Michael A. Gennert; Gretar Tryggvason; James Van de Ven

neutralprime condition where participants were informed we were interested in generalexperiences while participating in FIRST. Length of Time Manipulation. To examine if length of time while participating inFIRST influenced participants’ social networking skills, we administered the survey atthe beginning of the FIRST robotics season and again at the end of the season. Theseason started in mid-January and ended in mid-April; thus there were approximately 3-4months from the beginning of the season to the end of the season. Self-Efficacy Measure. To see if participating in FIRST influenced self-efficacy, orthe belief that one is capable of performing in a certain manner to attain certain goals, wemeasured their academic and social self

Conference Session

IE and the Classroom

Collection

2010 Annual Conference & Exposition

Authors

Lesley Strawderman, Mississippi State University; Laura Ruff, Mississippi State University

Tagged Divisions

Industrial Engineering

retention rates, degree attainment, and grade point averages, additionalliterature suggests that students’ efficacy beliefs may be an important measure of courseeffectiveness5. Self-efficacy, as first described by Bandura6, can positively or negativelyinfluence behavior based on a person’s perception of his abilities to successfully complete a task.Self-efficacy beliefs of undergraduate students in STEM (i.e. Science, Technology, Engineeringand Mathematics) majors have been linked to success and persistence within these fields7.Additionally, self-efficacy beliefs have been shown to affect interest, expectations, and choicesof engineering students8-9.Previous work examined self-efficacy beliefs of students in relation to their expectations

Conference Session

Students' Abilities and Attitudes

Collection

2010 Annual Conference & Exposition

Authors

Chih Hsien Huang, MingChi University of Technology

Tagged Divisions

Mathematics

behavior domainsexplore the relation between attitude and its internal factors of calculus learning amongengineering students in Taiwan. This study used theory and related research to develop aquestionnaire research tool. The internal factors of calculus learning that we choose wereusefulness, self-efficacy, motivation, anxiety, and, learning habits. The contributions of thisstudy are as follows The findings show that a high percentage of students do not havepositive attitudes toward calculus. A statistical significant difference existed in the meanscores for males and females in the calculus attitudes scale. Specifically, statistical significantdifferences were detected between males and females in two attitude domains: cognitive andbehavior. The

Conference Session

NSF Grantees Poster Session

Collection

2010 Annual Conference & Exposition

Authors

Lisa Schneider, Cornell University; Maria Terrell, Cornell University Math Dept.

nine workshops per semester rather thanfourteen, and one problem per workshop rather than two.During the Fall 2009 semester we ran a pilot pre- and post-test administration of the first draft ofboth assessment instruments – one measuring students’ abilities to use mathematics in appliedproblem-solving (MAI); and the other to gauge students' self-efficacy perceptions related tostudying engineering and to learning and applying mathematics (EMPS). The instrumentdevelopment and pilot-test administration processes are described in the following sections.Instrument Development:Mathematics Applications Inventory (MAI)The Mathematics Applications Inventory, MAI, is intended to measure the level at which firstyear undergraduate engineering students can

Conference Session

Sustainability in Engineering Curricula

Collection

2010 Annual Conference & Exposition

Authors

Mary McCormick, Tufts University; Kristina Lawyer, Michigan Technological University; Meredith Berlin, University of Colorado - Boulder; Chris Swan, Tufts University; Kurt Paterson, Michigan Technological University; Angela Bielefeldt, University of Colorado, Boulder; Jonathan Wiggins, University of Colorado, Boulder

Tagged Divisions

Environmental Engineering

engineering design is unclear. The objective of thisresearch is to measure whether students who have service learning experience have a deeperunderstanding of sustainable engineering than their counterparts who do not have servicelearning experience. The research design is comprised of three evaluations: sustainableengineering design, self-efficacy towards sustainable engineering, and epistemological beliefstowards general engineering. Each evaluation will be performed on engineering students at threedifferent institutions which employ varying types of service learning programs; Tufts University,Michigan Technological University, and University of Colorado-Boulder. Students enrolled inthe Civil and Environmental Engineering Senior Design/Capstone

Conference Session

Student Poster Session

Collection

2010 Annual Conference & Exposition

Authors

Joe Jien-Jou Lin, Purdue University; P.K. Imbrie, Purdue University; Qu Jin, Purdue University

Tagged Divisions

Students Constituent Committee

test scores, and thegrades and number of semesters in math, science and English courses in high school. The non-cognitive variables were collected through Student Attitudinal Success Instrument (SASI). Thefirst phase of SASI covered the following nine constructs: Leadership, Deep Learning, SurfaceLearning, Teamwork, Academic Self-efficacy, Motivation, Meta-cognition, Expectancy-value,and Major Decision. Later in 2007, five new constructs were added into SASI. These newconstructs are: Goal Orientation, Implicit Beliefs, Intent to Persist, Social Climate and SelfWorth.Cognitive and non-cognitive data, as well as students’ retention status after first year have beencollected from the freshman cohorts of 2004-2009, with 1500 to 1700 entering

Conference Session

The Influence of Cooperative Education

Collection

2010 Annual Conference & Exposition

Authors

Alexander Yin, Pennsylvania State University

Tagged Divisions

Cooperative & Experiential Education

manipulation of information isgoal-directed. The ease of this process is dependent on the engineer’s level of expertise incontent knowledge (declarative knowledge) and procedural knowledge (i.e., she knows when touse a particular algorithm, formula or process) (d and e). Evaluation of the process andjudgments of alternative outcomes (i) may be influenced by the engineer’s personal skills andbias on whether the project is a success or not (i.e., maybe the bridge met the functionalspecifications but failed from an aesthetic perspective).Self-Perception of Problem-Solving Skills Bandura's self-efficacy theory postulates that an individual’s confidence rises when hehas mastered a skill through experiencexx. Self-efficacy studies in STEM fields

Conference Session

Engineering Professional Development for K-12 Teachers

Collection

2010 Annual Conference & Exposition

Authors

Elsa Head, Tufts University; Adam Carberry, Tufts University

Tagged Divisions

K-12 & Pre-College Engineering

-teachercollaboration can provide teachers with the expertise and tools necessary to overcome lowconfidence, which may inhibit their ability and willingness to teach these topics.5For the purposes of this paper, we will be examining aspects of STOMP regarding K-12teachers’ acquisition of STEM content knowledge. We will specifically look at engineering andtechnology, which are the most recent additions to the Massachusetts’ Curriculum Frameworks.2We will take a closer look at the three-phase model that governs the program and the roles of theK-12 teacher. We will also investigate how this program affects teacher self-efficacy,perceptions, and interest regarding the teaching of engineering and technology.Theoretical FrameworkTo ensure that teachers gradually

Conference Session

Teams and Teamwork in Design

Collection

2010 Annual Conference & Exposition

Authors

Senay Purzer, Purdue University

Tagged Divisions

Design in Engineering Education

AC 2010-1446: THE MERIT KIT: METHODS FOR EVALUATING ROLES ANDINTERACTIONS IN TEAMSSenay Purzer, Purdue University Senay Purzer is an Assistant Professor in the School of Engineering Education at Purdue University. She is also the Co-Director of Assessment Research for the Institute for P-12 Engineering Research and Learning (INSPIRE). She received a Ph.D. and a M.A in Science Education, Department of Curriculum and Instruction from Arizona State University. Her creative research focuses on collaborative learning, design & decision-making, and the role of engineering self-efficacy on student achievement

Conference Session

Thermodynamics, Fluids, and Heat Transfer-Part I

Collection

2010 Annual Conference & Exposition

Authors

Simin Hall, College of Engineering at Virginia Tech; Catherine Amelink, Virginia Tech; Sam Conn, Virginia Tech

Tagged Divisions

Mechanical Engineering

the 45 students enrolled in the course, 35 (29 men, 6 women) students completed the survey.Mean scores were computed for each item on the survey. Factor analysis was used to developthree scales for the three constructs measured by the survey. Chronbach alpha scores were usedto ensure reliability for the three scales. The mean age for the 35 students were 20.5 (SD=.92).C. Results from Survey:C.1. Self-EfficacyThe mean of self-efficacy in problem solving was 4.23 (SD=.54) for all 35 students with areliability coefficient of 0.82. Therefore, they were confident about their general problem solvingskills in engineering courses, revealing a high degree of self-efficacy. The mean and standarddeviation for each item that comprised the scale is shown

Conference Session

NSF Grantees Poster Session

Collection

2010 Annual Conference & Exposition

Authors

Jacquelyn Kelly, Arizona State University; Aaron Graham, Arizona State University; Andrea Eller, Arizona State University; Dale Baker, Arizona State University; Amaneh Tasooji, Arizona State University; Stephen Krause, Arizona State University

here on theresearch question of, “How can we use class reflections to support student learning, attitude, andretention?” Assessment of the Class Reflection Points through emergent themes coding indicatesthat responses to the Most Interesting Point show students' quite active engagement in content,activities, and team member interactions. The Muddiest Point shows confusion, uncertainty, orlack of self efficacy on sometimes a narrow content slice, sometimes scattered concepts ofconfusion, and sometimes no muddiest point at all. The instructor is frequently surprised that hisperception of his clarity of content concept and presentation that do not always align with studentcomments. Analysis of the Take Away Point indicates responses are strongly

Conference Session

Engaging Students in Learning

Collection

2010 Annual Conference & Exposition

Authors

HuiRu Shih, Jackson State University; Wei Zheng, Jackson State University; Tzusheng Pei, Jackson State University; Gordon Skelton, Jackson State University; Evelyn Leggette, Jackson State University

Tagged Divisions

Engineering Technology

, especially, self-efficacy.6.1 Expandable IntelligenceOne important aspect in SRL is to regulate the learners’ motivation. Psychological instructionmodel of Expandable Intelligence (EI) is established based on new psychological findings thatlearners’ belief on their intelligence has a profound influence on their motivation to learn. Withthe belief that intelligence can be expanded (as opposed to the view of fixed intelligence),learners are able to attribute their successes or failures to factors within their control (e.g. efforton a task, or effective use of strategies) rather than their ability. They can be motivated to uselearning strategies and persist in their learning efforts for expanding their intelligence21.6.2 Enhance Students’ MotivationAs

Conference Session

Mentoring & Outreach for Girls & Minorities

Collection

2010 Annual Conference & Exposition

Authors

Keith Holbert, Arizona State University; Lisa Grable, North Carolina State University; Patricia Dixon, Florida State University; Sharon Schulze, North Carolina State University

Tagged Divisions

K-12 & Pre-College Engineering

Institutional Review Board at each university, with anapplication package including the survey instruments and informed consent letters for teachersand students. In addition to quantitative measures of participation and diversity, the assessmentincludes attitudinal measures of problem-solving and self-efficacy.8,9,10 Also, qualitativereflections completed by teachers, Young Scholars, and middle school students are collectedonline at the completion of each activity. Mentors and ERC precollege staff perform Page 15.969.6longitudinal follow-up electronically. This follow-up itself may have a positive effect onprecollege participants, helping them see

Conference Session

Teaching Mechanical Systems: What's New

Collection

2010 Annual Conference & Exposition

Authors

Ashok Kumar Manoharan, Auburn University; P.K. Raju, Auburn University; Chetan Sankar, Auburn University

Tagged Divisions

Mechanical Engineering

concepts. Inaddition, three case studies were used in the experimental section. Four class periods were setaside for presenting and discussing case studies. The assessment of student learning in both institutions was conducted through the use ofa questionnaire that measured the students’ perceptions on achieving higher-order cognitiveskills, improvement in self-efficacy, and improvement in team working skills11. Thesequestionnaires were completed by the students in the experimental and control sections at thestart and end of the course. The items in the questionnaire were combined to compute the meansand standard deviation of the measures. Table 2 shows the results that were computed for theexperimental and control sections at both Auburn

Conference Session

Aerospace Technical Session

Collection

2010 Annual Conference & Exposition

Authors

Edward Crawley, MIT; Robert Niewoehner, United States Naval Academy; Jean Koster, University of Colorado, Boulder

Tagged Divisions

Aerospace

development skills necessary to translate technicalknowledge into competitive products; and self confidence in learning (self-efficacy). We’ve introduced the innovative adaptation of new tools for student learning assessment toaeronautics education. Assessment of self-confidence in learning will be used both as animportant educational outcome and as a means to better understand the dynamics of careerdevelopment. There is a rich literature that has addressed the importance of having self-confidence that one can successfully perform the tasks necessary to achieve larger goals. Thisform of self-confidence, called self-efficacy,22 is not a general personality trait like self-esteem,but instead varies from one domain to another as individuals gain

Conference Session

NSF Grantees Poster Session

Collection

2010 Annual Conference & Exposition

Authors

Robert Culbertson, Arizona State University; Dale Baker, Arizona State University; Janice Meyer Thompson, Arizona State University; Christopher Mehrens, Arizona State University; Stephen Krause, Arizona State University

co-editor of the Journal of Research in Science Teaching. She has experience in the evaluation of a number of NSF projects including a Bridging Engineering and Education and a current TPC program. She has been a faculty member in science curriculum and instruction and has taught and developed courses in assessment, equity, and bridging engineering and education. She has been involved in the development of innovative science teaching curricular activities and is a co-PI of an NSF TPC project that is providing community college science teachers with authentic science inquiry and writing experiences. She is contributing to the effective formative and summative assessment of self-efficacy

Conference Session

Think Outside the Box! K-12 Engineering Curriculum

Collection

2010 Annual Conference & Exposition

Authors

Heath Tims, Louisiana Tech University; Krystal Corbett, Louisiana Tech University; Galen Turner, Louisiana Tech University; David Hall, Louisiana Tech University

Tagged Divisions

K-12 & Pre-College Engineering

-world applications of science and engineering. This project provides a hands-on, contextualapproach to student learning, as well as teacher professional development. As part of thecurriculum, data is being collected on student outcomes that quantify high school students’academic self-efficacy, real world problem solving, critical thinking skills, achievement inmathematics and the sciences, motivational and goal orientation, and vocational or careerinterests in STEM fields. Additionally, teacher outcomes, including self-efficacy, are beingmeasured. This poster/paper will present the curriculum developed through the collaborativepartnership between K12 schools systems and university.IntroductionNumerous publications in recent years have expressed

Conference Session

Teaching Mechanics of Materials & General Mechanics

Collection

2010 Annual Conference & Exposition

Authors

Shaobo Huang, Utah State University; Ning Fang, Utah State University

Tagged Divisions

Mechanics

, allowing education researchers andpractitioners to “see” how the predicted results are generated, and thus the predicted results canbe interpreted in a reasonable and meaningful way 11. For example, Green 12 developed a set oflinear regression models for three mechanical engineering courses to predict a student’s finalexam score from the student’s scores in mid-term quizzes. A modest correlation was foundbetween a student’s final exam score and mid-term exam scores. Yousuf 13 developed amultivariate linear regression model to predict student academic performance in ComputerScience and Engineering Technology programs. The predictor/independent variables ofYousuf’s model 13 included a student’s career self-efficacy belief, math-SAT scores, high

Conference Session

Teacher and Counselor Professional Development

Collection

2010 Annual Conference & Exposition

Authors

Laura Bottomley, North Carolina State University; Justin Osterstrom, Combs Elementary Scho

Tagged Divisions

K-12 & Pre-College Engineering

this data is quite timely, because this course isunique among offerings across the country. The pre-service teachers in the class represented avariety of backgrounds, but generally displayed lower self-efficacy than engineering students oftheir age. The general lack of understanding of such students with regards to engineering,including the differences and similarities among the various STEM disciplines as well as theirown feelings of fear and/or inadequacy when faced with problem solving tasks may represent asignificant barrier to the potential recruiting success of future engineering students. This paperwill describe the results of self-efficacy assessments, the methods used in presentation of thecourse material and the ways in which the